AI that earns its place in your product.
We build AI features that actually move metrics — copilots, recommendation systems, autonomous workflows — engineered with the same rigour as the rest of your product.
The Problem
"Powered by AI" labels with no measurable impact
Hallucinations that erode user trust within weeks
No evals, no guardrails, no observability
Prompt spaghetti instead of real engineering
Our Approach
Every AI feature we ship has evals, guardrails, fallback paths, and clear KPIs. We treat models like any other dependency — version-controlled, observable, replaceable.
No feature ships without a measurable quality bar.
Input validation, output filtering, safety classifiers built in.
RAG, structured tools, and fine-tuning combined where each wins.
Every prompt, response, and decision logged and queryable.
What You Get
Built With
Models
Orchestration
Retrieval
Ops
Timeline
Week 1
Identify highest-leverage AI surfaces with clear KPIs.
Week 2–3
Working spike against a real eval set.
Week 3–6
Guardrails, observability, integration.
Week 6–8
A/B against baseline, iterate on prompts + retrieval.
Week 8+
Eval suite, runbook, knowledge transfer.
Selected client launches
Questions
Whichever wins on your eval set. We benchmark across providers and pick per-feature.
Through grounded retrieval, structured outputs, validators, and human-in-the-loop where the cost of wrong is high.
We design with cost budgets per request and monitor spend in real time. Caching + routing keep costs predictable.
Pairs Well With
Let's build